Error Correction Method Study Of An Combination Array In The Near Field

High-resolution spatial spectrum estimation algorithms obtain higher performance, as a precondition which array manifold are precisely known.If array manifold is not precise as some array errors,the performance of high-resolution spatial spectrum estimation algorithms will decline seriously ,even disabled. In practical engineering applications,due to the limit of production process, instrument accuracy or other factors,array errors are almost inevitable which is the obstacle that makes high-resolution spatial spectrum estimation go from theory to practical restrictions. This article starts from the practical engineering application,in order to get a method to revise array sensitivity error, position error and axial deflection error when they exist together.This paper establish a combined array near-field data model,infer the theory high-resolution spatial spectrum estimation algorithms(MUSIC), verify the validation that combined linear array inhibit string fuzzy.by comparing with simulation analysis of acoustic linear array, verify the high resolution performance of MUSIC algorithm by comparing with simulation analysis of MVDR algorithm.This paper has established a the far-field array error model, array errors include:sensitivity error, position error, axial deflection errors. Discuss the condition of each error exist alone and the coexistence of three kinds of error espectively,verify the affect of each error to the performance of MUSIC algorithm positioning. Put forward a far-field array error correction method, discuss the accuracy of this peper algorithm for each array error parameter estimation in different SNR conditions.In order to overcome the layout difficulty of the far-field auxiliary source and the characteristics of the acoustic energy attenuation in the process of transmission. Put forward a method to revise array errors in the near field, establish a the near-field array error model,array errors include: sensitivity error, position error, axial deflection errors. Discuss the accuracy of this peper algorithm for each array error parameter estimation in different SNR conditions, do 100 times monte karlo experiment, verify the statistical results of error parameter estimation. Discuss the change of each error parameters estimation precision when the frequency of auxiliary source change, do 100 times monte karlo experiment, verify the statistical results of error parameter estimation. analysis the calibration correction ability of the algorithm when change the amplitude of array error parameters.